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1 |
Accounting research and the significance test crisis
تحقیقات حسابداری و بحران آزمون اهمیت-2021 The emerging or at least threatening ‘‘significance test crisis” in accounting has been
prompted by a chorus across multiple physical and social sciences of dissatisfaction with
conventional frequentist statistical research methods and behaviors, particularly the use
and abuse of p-levels. There are now hundreds of published papers and statements,
echoing what has been said behind closed doors for decades, namely that much if not
most empirical research is unreliable, simply wrong or at worst fabricated. The problems
are a mixture of flawed statistical logic (as Bayesians have claimed for decades), ‘‘phacking” by way of fishing for significant results and publications, selective reporting or
‘‘the file drawer problem”, and ultimately the ‘‘agency problem” that researchers charged
by funding bodies (their Universities, governments and taxpayers) with conducting
disinterested ‘‘objective science” are motivated more by the personal need to publish
and please other researchers. Expanding on that theme, the supply of empirical research
in the ‘‘market for statistical significance” is described in terms of ‘‘market failure” and
‘‘the market for lemons”.
keywords: تحقیق حسابداری تجربی | آزمایشات | بحران تکثیر | سطحی | گزارش های ثبت شده | Empirical accounting research | Significance tests | Replication crisis | p-levels | p-hacking | Registered reports |
مقاله انگلیسی |
2 |
Optimizing the electrical conductivity of polyacrylonitrile/polyaniline with nickel nanoparticles for the enhanced electrostimulation of Schwann cells proliferation
بهینه سازی رسانایی الکتریکی پلی اکریلونیتریل/پلی آنیلین با نانوذرات نیکل برای تحریک الکتریکی افزایش یافته تکثیر سلول های شوان-2021 Tissue engineering scaffolds made of biocompatible polymers are promising alternatives for nerve reparation. For this application, cell proliferation will be speeded up by electrostimulation, which required
electrically-conductive materials. Here, a biomimicking scaffold with optimized conductivity was developed from electrospun polyacrylonitrile/electrically-conductive polyaniline (PAN/PANI) nanofibers
doped with Ni nanoparticles. PAN/PANI/Ni was biocompatible for Schwann cells and exhibited a suitable
tensile strength and wettability for cell proliferation. When compared with unmodified PAN/PANI, the
electrical conductivity of PAN/PANI/Ni was 6.4 fold higher. Without electrostimulation, PAN/PANI and
PAN/PANI/Ni exhibited similar Schwann cells’ proliferation rates. Upon electrostimulation at
100 mV cm1 for one hour per day over five days, PAN/PANI/Ni accelerated Schwann cells’ proliferation
2.1 times compared to PAN/PANI. These results demonstrate the importance of expanding the electrical
conductivity of the tissue engineering scaffold to ensure optimal electrostimulation of nerve cell growth.
Additionally, this study describes a straightforward approach to modulate the electrical conductivity of
polymeric materials via the addition of Ni nanoparticles that can be applied to different biomimicking
scaffolds for nerve healing.
Keywords: Nerve tissue engineering | Electrospinning | PAN/PANI | Ni nanoparticles | Schwann cells |
مقاله انگلیسی |
3 |
18: Data deduplication applications in cognitive science and computer vision research
18: کاربردهای تکثیر داده ها در علوم شناختی و تحقیقات بینایی ماشین-2021 Advances in technologies in the field of computing and semiconductor research have made the
devices and gadgets portable, which are used in all modern applications ranging from healthcare
to robotics and self-driving car. These applications require capturing huge amount of information
through various sensors in the form of images, videos, and other physical stimuli. If the data are in
the form of images or videos, then the storage becomes a matter of concern. Some image processing is involved where images are processed using suitable signal processing systems and components. The typical computer vision (CV) system that actually mimics human vision system is
shown in Fig. 181. We can see in the figure that some stimuli indicated by some physical excitation is captured by sensors and sent for preprocessing to make the captured data appropriate for
further operation. Once the data become proper for specific application, it is subjected to some
machine learning methods or artificial intelligence for understanding of the data. This may be
used as the process for learning the data and getting some suitable features that would be used in
postprocessing of the data. CV then classifies the data and outputs some decisions or commands
depending on the applications. The data that are used in CV are mainly of image types and the
operation is image processing.
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مقاله انگلیسی |
4 |
شدت و پتانسیل انتقال کرونا در کره جنوبی
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 14 اهداف: ازآنجایی که اولین مورد کروناویروس جدید 2019(کوید-19) در 20 ژانویۀ 2020 در کرۀ شمالی شناسایی شد، تعداد موارد به سرعت افزایش یافت به طوری که تا 6 مارس 2020، منجربه ابتلای6284 مورد و فوت42 نفر شد. اولین تحقیق درمورد گزارش تعداد تکثیر کوید-19 در کرۀ جنوبی را برای بررسی سرعت شیوع بیماری، ارائه می دهیم.
روش کار: موارد روزانۀ تأیید شدۀ کوید-19 در کرۀ جنوبی از منابع عمومی موجود استخراج شد. با استفاده از توزیع تجربی گزارشات دارای تأخیر و شبیه سازی مدل رشد کلی، تعداد تکثیر مؤثر را برمبنای توزیع احتمال گسستۀ فاصلۀ زایشی ارزیابی کردیم. نتایج: چهار گروه اصلی را شناسایی و تعداد تکثیر را 1.5(1.6-1.4 CI: 95%) برآورد کردیم. به علاوه، نرخ رشد طبیعی 0.6 (0.7، 0.6 CI: 95%) و مقیاس بندی پارامتر رشد 0.8 (0.8،0.7 CI: 95%) برآورد شدند، که نشان-دهندۀ پویایی رشد زیر نمایی کوید-19 می باشد. نرخ مرگ و میر موارد خام در بین مردان (1.1%) در مقایسه با زنان (0.4%) بیشتر است و با افزایش سن افزایش می یابد. نتیجه گیری: نتایج ما انتقال پایدار اولیۀ کوید-19 در کرۀ جنوبی را نشان می دهد و از اجرای اقدامات فاصله گذاری اجتماعی برای کنترل سریع شیوع بیماری حمایت می کند. کلمات کلیدی: کروناویروس | کوید-19 | کره | تعداد تکثیر |
مقاله ترجمه شده |
5 |
Contracts as reference points: A replication
قراردادها به عنوان نقاط مرجع: یک تکرار-2020 We replicate two treatments of an experimental theory test (Fehr et al., 2011) studying Hart and Moore
(2008)’s idea that contracts serve as reference points in trading relationships. In contrast to rigid contracts,
flexible contract terms may be perceived in a self-serving manner and, therefore, the contract parties
might form subjective entitlements. This reference-dependent perception of flexible contract terms leads
to a trade-off of the contractual form. While flexible contracts are, in theory, deemed preferable to rigid
contracts, frustrated subjective entitlements may lead to perfunctory performance and shading behavior
that is absent in rigid contracts. The results of our replication are mixed. Our findings imply further support for Hart and Moore (2008)’s contracts as reference point hypothesis. However, our replication does
not provide reliable evidence for the idea that competition creates objectivity and enhances perceived
fairness of the contract terms.
Keywords: Contract theory | Reference points | Self-serving bias | Laboratory experiment | Replication | Bayesian statistics |
مقاله انگلیسی |
6 |
Using retracted journal articles in psychology to understand research misconduct in the social sciences: What is to be done?
استفاده از مقالات مجله جمع شده در روانشناسی برای درک سوء رفتار پژوهشی در علوم اجتماعی: چه کاری باید انجام شود؟-2020 This paper explores the nature and impact of research misconduct in psychology by analyzing 160 articles that were retracted from prominent scholarly journals between 1998 and 2017. We compare findings with recent studies of retracted papers in economics, and business and management, to profile practices that are likely to be problematic in cognate social science disciplines. In psychology, the principal reason for retraction was data fabrication. Retractions took longer to make, and generally were from higher ranked and more prestigious journals, than in the two cognate disciplines. We recommend that journal editors should be more forthcoming in the reasons they provide for article retractions. We also recommend that the discipline of psychology gives a greater priority to the publication of replication studies; initiates a debate about how to respond to failed re- plications; adopts a more critical attitude to the importance of attaining statistical significance; discourages p- hacking and Hypothesizing After Results are Known (HARKing); assesses the long-term effects of pre-registering research; and supports stronger procedures to attest to the authenticity of data in research papers. Our con- tribution locates these issues in the context of a growing crisis of confidence in the value of social science research. We also challenge individual researchers to reassert the primacy of disinterested academic inquiry above pressures that can lead to an erosion of scholarly integrity. Keywords: Misconduct | Psychology | Research | Replication | Retractions |
مقاله انگلیسی |
7 |
چارچوبی برای تحقیقات بازاریابی دیجیتال: بررسی چهار عصر فرهنگی بازاریابی دیجیتال
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 19 - تعداد صفحات فایل doc فارسی: 27 رشته بازاریابی دیجیتال با گسستگی فزاینده مواجه شده است؛ تکثیر زمینه های فرعی مختلف تحقیق مانع از تجمع دانش می گردد. این گسستگی به نظر می رسد متکی به پیچیدگی ذاتی اینترنت بوده و حاصل 50 سال تکامل است. هدف ما فراهم سازی چارچوب یکپارچه برای تحقیقات در بازاریابی دیجیتالی برگرفته از تحلیل تاریخی اینترنت است. با استفاده از نظریه تمرین و نظریه موسساتی، نوع جدید کار موسساتی را طراحی می کنیم. این چارچوب را برای تحلیل منابع ثانویه تاریخی به کار می بریم. چهار گروه فرهنگی در اینترنت (سیستم های مشارکتی، سیستم هایبازار سنتی، سیستم های تولید مشترک و سیستم بازار تولید مصرف) یافته و به توصیف اصول پویا نحوه ایجاد سیستم ها با همگون سازی مجموعه فرهنگی موجود می پردازیم. با فراهم سازی چارچوب فرهنگی نظریه ای که اصول پویا ایجاد چهار مجموعه فرهنگی، به ادبیات بازاریابی دیجیتال می افزاییم. به علاوه، سه مسیر تکامل بالقوه نمای دیجیتال را مطرح می کنیم. چارچوب ما ممکن است به مدیران کمک کند تا از راهبرد دیجیتالی خود سر درآورند و در سیستم های اینترنت مختلف جستجو کنند.
کلمات کلیدی: بازاریابی دیجیتال | روش تاریخی | فرهنگ های دیجیتال | نظریه نهادی | تئوری تمرین | چارچوب فرهنگی | آینده نگر |
مقاله ترجمه شده |
8 |
N3-CPL: Neuroplasticity-based Neuromorphic Network Cell Proliferation Learning
N3-CPL: یادگیری تکثیر سلولی شبکه عصبی مبتنی بر Neuroplasticity-2020 Recent deep neural networks have brought tremendous changes and advancements in many areas. The neural
networks are built mainly in the black box form, with complex combinations of continuous nonlinear function
values and weighted input values. The reason why these combinations are called ‘neural networks’ is that they
are inspired by the biological structure of the human brain. The biggest feature of the neural network is that it
enables the use of a gradient-based optimization method for the training, by building a huge nonlinear function.
Recently, the large-scale labeled dataset construction, the increase in innovative computing resources, and the
development of advanced regularization methods have given the neural networks an excellent modeling ability to
generalize the data that is difficult to analyze, thereby making huge progress in the network performance. |
مقاله انگلیسی |
9 |
Vibrational mono-/bi-resonance and wave propagation in FitzHugh–Nagumo neural systems under electromagnetic induction
تک لرزش و تکثیر ارتعاش و انتشار موج در سیستم های عصبی FitzHugh–Nagumo تحت القای الکترومغناطیسی-2020 In this paper, an modified FitzHugh–Nagumo (FHN) neural model was employed to investigate the vibra- tional resonance (VR) phenomenon, the collective behaviors, and the transmission of weak low-frequency (LF) signal driven by high-frequency (HF) stimulus under the action of different electromagnetic induction in single FHN neuron and feed-forward feedback network (FFN) system, respectively. For the single FHN system, by increasing the amplitude of HF stimulus, the phenomena of vibrational mono-/bi-resonance are observed, and the input weak signal and output of system are synchronized, and the information of the weak LF signal is amplified. For the FFN system, the phenomena of vibrational mono-/bi-resonances are also occurred, both frequency and amplitude of the HF stimulus play an important role in the vibra- tional bi-resonances and transmission of weak LF signal in the FHN neural FFN. Keywords: Vibrational resonance | FitzHugh–Nagumo model | Feed-forward feedback | neural network Electromagnetic induction | Chaos and bifurcation analysis |
مقاله انگلیسی |
10 |
Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer
استراتژی رادیومیک مبتنی بر یادگیری ماشین برای پیش بینی تکثیر سلولی در سرطان ریه سلول غیر کوچک-2019 Purpose: To explore the feasibility and performance of machine learning-based radiomics classifier to predict the
cell proliferation(Ki-67)in non-small cell lung cancer (NSCLC).
Methods: 245 histopathological confirmed NSCLC patients who underwent CT scans were retrospectively included.
The Ki-67 proliferation index (Ki-67 PI) were measured within 2 weeks after CT scans. A lesion volume of
interest (VOI) was manually delineated and radiomics features were extracted by MaZda software from CT
images. A random forest feature selection algorithm (RFFS) was used to reduce features. Six kinds of machine
learning methods were used to establish radiomics classifiers, subjective imaging feature classifiers and combined
classifiers, respectively. The performance of these classifiers was evaluated by the receiver operating
characteristic curve (ROC) and compared with Delong test.
Results: 103 radiomics features were extracted and 20 optimal features were selected using RFFS. Among the
radiomics classifiers established by six machine learning methods, random forest-based radiomics classifier
achieved the best performance (AUC=0.776) in predicting the Ki-67 expression level with sensitivity and
specificity of 0.726 and 0.661, which was better than that of subjective imaging classifiers (AUC=0.625,
P < 0.05). However, the combined classifiers did not improve the predictive performance (AUC=0.780,
P > 0.05), with sensitivity and specificity of 0.752 and 0.633.
Conclusions: The machine learning-based CT radiomics classifier in NSCLC can facilitate the prediction of the
expression level of Ki-67 and provide a novel non-invasive strategy for assessing the cell proliferation. Keywords: Non-small cell lung cancer (NSCLC) | Ki-67 | CT | Radiomics | Machine learning |
مقاله انگلیسی |